Search results for "Handbook of Computer Programming with Python"
Items we need to order for you
Introduction to Digital Music with Python Programming
Introduction to Digital Music with Python Programming provides a foundation in music and code for the beginner. It shows how coding empowers new forms of creative expression while simplifying and automating many of the tedious aspects of production and composition.With the help of online, interactive examples, this book covers the fundamentals of rhythm, chord structure, and melodic composition alongside the basics of digital production. Each new concept is anchored in a real-world musical example that will have you making beats in a matter of minutes.Music is also a great way to learn core programming concepts such as loops, variables, lists, and functions, Introduction to Digital Music with Python Programming is designed for beginners of all backgrounds, including high school students, undergraduates, and aspiring professionals, and requires no previous experience with music or code.
R 2,125.92
Programming with 64-Bit ARM Assembly Language
Mastering ARM hardware architecture opens a world of programming for nearly all phones and tablets including the iPhone/iPad and most Android phones. It’s also the heart of many single board computers like the Raspberry Pi. Gain the skills required to dive into the fundamentals of the ARM hardware architecture with this book and start your own projects while you develop a working knowledge of assembly language for the ARM 64-bit processor.You'll review assembly language programming for the ARM Processor in 64-bit mode and write programs for a number of single board computers, including the Nvidia Jetson Nano and the Raspberry Pi (running 64-bit Linux). The book also discusses how to target assembly language programs for Apple iPhones and iPads along with 64-Bit ARM based Android phones and tablets. It covers all the tools you require, the basics of the ARM hardware architecture, all the groups of ARM 64-Bit Assembly instructions, and how data is stored in the computer’s memory. In addition, interface apps to hardware such as the Raspberry Pi’s GPIO ports. The book covers code optimization, as well as how to inter-operate with C and Python code. Readers will develop enough background to use the official ARM reference documentation for their own projects.With Programming with 64-Bit ARM Assembly Language as your guide you’ll study how to read, reverse engineer and hack machine code, then be able to apply these new skills to study code examples and take control of both your ARM devices’ hardware and software. What You'll LearnMake operating system calls from assembly language and include other software libraries in your projectsInterface apps to hardware devices such as the Raspberry Pi GPIO portsReverse engineer and hack codeUse the official ARM reference documentation for your own projectsWho This Book Is ForSoftware developers who have already learned to program in a higher-level language like Python, Java, C#, or even C and now wish to learn Assembly programming.
R 1,311.94
Expert Python Programming
Gain a deep understanding of building, maintaining, packaging, and shipping robust Python applicationsKey FeaturesDiscover the new features of Python, such as dictionary merge, the zoneinfo module, and structural pattern matchingCreate manageable code to run in various environments with different sets of dependenciesImplement effective Python data structures and algorithms to write, test, and optimize codeBook DescriptionThis new edition of Expert Python Programming provides you with a thorough understanding of the process of building and maintaining Python apps. Complete with best practices, useful tools, and standards implemented by professional Python developers, this fourth edition has been extensively updated. Throughout this book, you’ll get acquainted with the latest Python improvements, syntax elements, and interesting tools to boost your development efficiency.The initial few chapters will allow experienced programmers coming from different languages to transition to the Python ecosystem. You will explore common software design patterns and various programming methodologies, such as event-driven programming, concurrency, and metaprogramming. You will also go through complex code examples and try to solve meaningful problems by bridging Python with C and C++, writing extensions that benefit from the strengths of multiple languages. Finally, you will understand the complete lifetime of any application after it goes live, including packaging and testing automation.By the end of this book, you will have gained actionable Python programming insights that will help you effectively solve challenging problems.What you will learnExplore modern ways of setting up repeatable and consistent Python development environmentsEffectively package Python code for community and production useLearn modern syntax elements of Python programming, such as f-strings, enums, and lambda functionsDemystify metaprogramming in Python with metaclassesWrite concurrent code in PythonExtend and integrate Python with code written in C and C++Who this book is forThe Python programming book is intended for expert programmers who want to learn Python’s advanced-level concepts and latest features.Anyone who has basic Python skills should be able to follow the content of the book, although it might require some additional effort from less experienced programmers. It should also be a good introduction to Python 3.9 for those who are still a bit behind and continue to use other older versions.
R 1,661.00
Hands-On Data Structures and Algorithms with Python
Learn to implement complex data structures and algorithms using PythonKey FeaturesUnderstand the analysis and design of fundamental Python data structuresExplore advanced Python concepts such as Big O notation and dynamic programmingLearn functional and reactive implementations of traditional data structuresBook DescriptionData structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail.By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.What you will learnUnderstand object representation, attribute binding, and data encapsulationGain a solid understanding of Python data structures using algorithmsStudy algorithms using examples with pictorial representationLearn complex algorithms through easy explanation, implementing PythonBuild sophisticated and efficient data applications in PythonUnderstand common programming algorithms used in Python data scienceWrite efficient and robust code in Python 3.7Who this book is forThis book is for developers who want to learn data structures and algorithms in Python to write complex and flexible programs. Basic Python programming knowledge is expected.
R 1,498.00
R 608.00
Simulation with Python
Understand the theory and implementation of simulation. This book covers simulation topics from a scenario-driven approach using Python and rich visualizations and tabulations. The book discusses simulation used in the natural and social sciences and with simulations taken from the top algorithms used in the industry today. The authors use an engaging approach that mixes mathematics and programming experiments with beginning-intermediate level Python code to create an immersive learning experience that is cohesive and integrated. After reading this book, you will have an understanding of simulation used in natural sciences, engineering, and social sciences using Python.What You'll LearnUse Python and numerical computation to demonstrate the power of simulationChoose a paradigm to run a simulationDraw statistical insights from numerical experimentsKnow how simulation is used to solve real-world problems Who This Book Is ForEntry-level to mid-level Python developers from various backgrounds, including backend developers, academic research programmers, data scientists, and machine learning engineers. The book is also useful to high school students and college undergraduates and graduates with STEM backgrounds.
R 1,254.00
R 1,464.00
R 580.00
Introduction to Modern Scientific Programming and Numerical Methods
The ability to use computers to solve mathematical relationships is a fundamental skill for anyone planning for a career in science or engineering. For this reason, numerical analysis is part of the core curriculum for just about every undergraduate physics and engineering department. But for most physics and engineering students, practical programming is a self-taught process.This book introduces the reader not only to the mathematical foundation but also to the programming paradigms encountered in modern hybrid software-hardware scientific computing. After completing the text, the reader will be well-versed in the use of different numerical techniques, programming languages, and hardware architectures, and will be able to select the appropriate software and hardware tool for their analysis.It can serve as a textbook for undergraduate courses on numerical analysis and scientific computing courses within engineering and physical sciences departments. It will also be a valuable guidebook for researchers with experimental backgrounds interested in working with numerical simulations, or to any new personnel working in scientific computing or data analysis.Key Features:Includes examples of solving numerical problems in multiple programming languages, including MATLAB, Python, Fortran, C++, Arduino, Javascript, and VerilogProvides an introduction to modern high-performance computing technologies including multithreading, distributed computing, GPUs, microcontrollers, FPGAs, and web "cloud computing"Contains an overview of numerical techniques not found in other introductory texts including particle methods, finite volume and finite element methods, Vlasov solvers, and molecular dynamicsA video of the author discussing the book can be accessed here: https://www.youtube.com/watch?v=KYn8aDKXlcs
R 2,711.00
Advanced Python Programming
Write fast, robust, and highly reusable applications using Python's internal optimization, state-of-the-art performance-benchmarking tools, and cutting-edge librariesKey FeaturesBenchmark, profile, and accelerate Python programs using optimization toolsScale applications to multiple processors with concurrent programmingMake applications robust and reusable using effective design patternsBook DescriptionPython's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages.In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level.This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models.The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming.You'll also understand the common problems that cause undesirable behavior in concurrent programs.Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable.By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.What you will learnWrite efficient numerical code with NumPy, pandas, and XarrayUse Cython and Numba to achieve native performanceFind bottlenecks in your Python code using profilersOptimize your machine learning models with JAXImplement multithreaded, multiprocessing, and asynchronous programsSolve common problems in concurrent programming, such as deadlocksTackle architecture challenges with design patternsWho this book is forThis book is for intermediate to experienced Python programmers who are looking to scale up their applications in a systematic and robust manner. Programmers from a range of backgrounds will find this book useful, including software engineers, scientific programmers, and software architects.
R 1,596.00
Advanced Applications of Python Data Structures and Algorithms
Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision.Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
R 7,924.74
Pragmatic Python Programming
Explore the world of programming languages through Python and learn the building blocks of writing programs. This book covers Python 3.10, explaining it through six key concepts. Each chapter contains a real-world example with practical advice and a section on advanced concepts. You'll start by reviewing the concept of expressions and functions, which are two of the core building blocks of programming languages. You'll then move on to object-oriented concepts to help gain a practical understanding of Python, along with a chapter on control flow constructs. The book also takes a close look at sequences, explaining constructs and additional types, and wraps up with a chapter on modules, focusing on how to use and create packages. Whether you’re new to programming or already an experienced developer, upon finishing this book, you will have a solid understanding of Python's state-of-the-art development features.What You Will LearnStudy the six main concepts of the programming languagesLearn how to use programming language constructs through examplesReview the core Python language notations and concepts.Start using Python as a working languageWho This Book Is ForSoftware developers wanting to gain professional core Python knowledge quickly, and non-developers wanting to gain an understanding of programming concepts.
R 1,026.00
Competitive Programming in Python
Want to kill it at your job interview in the tech industry? Want to win that coding competition? Learn all the algorithmic techniques and programming skills you need from two experienced coaches, problem setters, and jurors for coding competitions. The authors highlight the versatility of each algorithm by considering a variety of problems and show how to implement algorithms in simple and efficient code. Readers can expect to master 128 algorithms in Python and discover the right way to tackle a problem and quickly implement a solution of low complexity. Classic problems like Dijkstra's shortest path algorithm and Knuth-Morris-Pratt's string matching algorithm are featured alongside lesser known data structures like Fenwick trees and Knuth's dancing links. The book provides a framework to tackle algorithmic problem solving, including: Definition, Complexity, Applications, Algorithm, Key Information, Implementation, Variants, In Practice, and Problems. Python code included in the book and on the companion website.
R 1,922.63
Python Programming Professional Made Easy
Python Programming Professional Made Easy 2nd Edition! Sam Key back at it again with his upgraded version of Python Going from beginner to professional? Want to skip the learning curve? Need the jargon removed so you can understand in your terms? From various programming languages to statements and Basic Operators Everything you need to know with functions and flow controls! Don't waste anytime and jump on board of Python! Start your programming right now!
R 1,039.00
R 519.00
R 560.00
Programming in Two Semesters
This highly accessible textbook teaches programming from first principles. In common with many programming courses, it uses Python as the introductory programming language before going on to use Java as the vehicle for more advanced programming concepts.The first part, which teaches Python, covers fundamental programming concepts, such as data types and control structures and functions. It introduces more complex data types such as lists and dictionaries and also deals with file handling. It introduces object-oriented concepts and ends with a case study bringing together all the topics of the first semester. The second part uses Java to teach advanced concepts and centres around object-oriented programming, teaching key object-oriented concepts such as inheritance and polymorphism. The semester again ends with an advanced case study bringing together all the topics of the second semester.Topics and features:Assumes no prior knowledge, and makes the transition from Python to Java a smooth processFeatures numerous exercises and also an illustrative case study for each language Examines procedural and object-oriented methodologies, as well as design principles Covers such advanced topics as interfaces and lambda expressions, exceptions and Collections Includes a chapter on graphics programming in Python using Tkinter Introduces the latest Java technology for graphical interfaces, JavaFXExplains design concepts using UML notation Offering a gentle introduction to the field and assuming no prerequisite background, Programming in Two Semesters is the ideal companion to undergraduate modules in software development or programming. In addition, it will serve as a strong primer for professionals looking to strengthen their knowledge of programming with these languages.
R 2,198.00
R 1,980.61
Concise Introduction to Programming in Python
A Concise Introduction to Programming in Python, Second Edition provides a hands-on and accessible introduction to writing software in Python, with no prior programming experience required.The Second Edition was thoroughly reorganized and rewritten based on classroom experience to incorporate: A spiral approach, starting with turtle graphics, and then revisiting concepts in greater depth using numeric, textual, and image data Clear, concise explanations written for beginning students, emphasizing core principles A variety of accessible examples, focusing on key concepts Diagrams to help visualize new concepts New sections on recursion and exception handling, as well as an earlier introduction of lists, based on instructor feedbackThe text offers sections designed for approximately one class period each, and proceeds gradually from procedural to object-oriented design. Examples, exercises, and projects are included from diverse application domains, including finance, biology, image processing, and textual analysis. It also includes a brief "How-To" sections that introduce optional topics students may be interested in exploring.The text is written to be read, making it a good fit in flipped classrooms. Designed for either classroom use or self-study, all example programs and solutions to odd-numbered exercises (except for projects) are available at: http://www.central.edu/go/conciseintro/.
R 1,330.00
R 1,008.00
R 704.00
R 580.00
Hands-On ROS for Robotics Programming
Take your ROS skills to the next level by implementing complex robot structures in a ROS simulationKey FeaturesLearn fundamental ROS concepts and apply them to solve navigation tasksWork with single board computers to program smart behavior in mobile robotsUnderstand how specific characteristics of the physical environment influence your robot’s performanceBook DescriptionConnecting a physical robot to a robot simulation using the Robot Operating System (ROS) infrastructure is one of the most common challenges faced by ROS engineers. With this book, you'll learn how to simulate a robot in a virtual environment and achieve desired behavior in equivalent real-world scenarios.This book starts with an introduction to GoPiGo3 and the sensors and actuators with which it is equipped. You'll then work with GoPiGo3's digital twin by creating a 3D model from scratch and running a simulation in ROS using Gazebo. Next, the book will show you how to use GoPiGo3 to build and run an autonomous mobile robot that is aware of its surroundings. Finally, you'll find out how a robot can learn tasks that have not been programmed in the code but are acquired by observing its environment. You'll even cover topics such as deep learning and reinforcement learning.By the end of this robot programming book, you'll be well-versed with the basics of building specific-purpose applications in robotics and developing highly intelligent autonomous robots from scratch.What you will learnGet to grips with developing environment-aware robotsGain insights into how your robots will react in physical environmentsBreak down a desired behavior into a chain of robot actionsRelate data from sensors with context to produce adaptive responsesApply reinforcement learning to allow your robot to learn by trial and errorImplement deep learning to enable your robot to recognize its surroundingsWho this book is forIf you are an engineer looking to build AI-powered robots using the ROS framework, this book is for you. Robotics enthusiasts and hobbyists who want to develop their own ROS robotics projects will also find this book useful. Knowledge of Python and/or C++ programming and familiarity with single board computers such as Raspberry Pi is necessary to get the most out of this book.
R 2,052.00
Numerical Computing with Python
Understand, explore, and effectively present data using the powerful data visualization techniques of PythonKey FeaturesUse the power of Pandas and Matplotlib to easily solve data mining issuesUnderstand the basics of statistics to build powerful predictive data modelsGrasp data mining concepts with helpful use-cases and examplesBook DescriptionData mining, or parsing the data to extract useful insights, is a niche skill that can transform your career as a data scientist Python is a flexible programming language that is equipped with a strong suite of libraries and toolkits, and gives you the perfect platform to sift through your data and mine the insights you seek. This Learning Path is designed to familiarize you with the Python libraries and the underlying statistics that you need to get comfortable with data mining.You will learn how to use Pandas, Python's popular library to analyze different kinds of data, and leverage the power of Matplotlib to generate appealing and impressive visualizations for the insights you have derived. You will also explore different machine learning techniques and statistics that enable you to build powerful predictive models.By the end of this Learning Path, you will have the perfect foundation to take your data mining skills to the next level and set yourself on the path to become a sought-after data science professional.This Learning Path includes content from the following Packt products:Statistics for Machine Learning by Pratap DangetiMatplotlib 2.x By Example by Allen Yu, Claire Chung, Aldrin YimPandas Cookbook by Theodore PetrouWhat you will learnUnderstand the statistical fundamentals to build data modelsSplit data into independent groups Apply aggregations and transformations to each groupCreate impressive data visualizationsPrepare your data and design models Clean up data to ease data analysis and visualizationCreate insightful visualizations with Matplotlib and SeabornCustomize the model to suit your own predictive goalsWho this book is forIf you want to learn how to use the many libraries of Python to extract impactful information from your data and present it as engaging visuals, then this is the ideal Learning Path for you. Some basic knowledge of Python is enough to get started with this Learning Path.
R 1,628.00
R 428.00
R 397.00
Introduction to Recursive Programming
Recursion is one of the most fundamental concepts in computer science and a key programming technique that allows computations to be carried out repeatedly. Despite the importance of recursion for algorithm design, most programming books do not cover the topic in detail, despite the fact that numerous computer programming professors and researchers in the field of computer science education agree that recursion is difficult for novice students. Introduction to Recursive Programming provides a detailed and comprehensive introduction to recursion. This text will serve as a useful guide for anyone who wants to learn how to think and program recursively, by analyzing a wide variety of computational problems of diverse difficulty.It contains specific chapters on the most common types of recursion (linear, tail, and multiple), as well as on algorithm design paradigms in which recursion is prevalent (divide and conquer, and backtracking). Therefore, it can be used in introductory programming courses, and in more advanced classes on algorithm design. The book also covers lower-level topics related to iteration and program execution, and includes a rich chapter on the theoretical analysis of the computational cost of recursive programs, offering readers the possibility to learn some basic mathematics along the way.It also incorporates several elements aimed at helping students master the material. First, it contains a larger collection of simple problems in order to provide a solid foundation of the core concepts, before diving into more complex material. In addition, one of the book's main assets is the use of a step-by-step methodology, together with specially designed diagrams, for guiding and illustrating the process of developing recursive algorithms. Furthermore, the book covers combinatorial problems and mutual recursion. These topics can broaden students' understanding of recursion by forcing them to apply the learned concepts differently, or in a more sophisticated manner.The code examples have been written in Python 3, but should be straightforward to understand for students with experience in other programming languages. Finally, worked out solutions to over 120 end-of-chapter exercises are available for instructors.
R 3,627.00
R 1,046.88
R 814.86
Network Programming and Automation Essentials
Unleash the power of automation by mastering network programming fundamentals using Python and Go best practicesPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesUnderstand the fundamentals of network programming and automationLearn tips and tricks to transition from traditional networking to automated networksSolve everyday problems with automation frameworks in Python and GoBook DescriptionNetwork programming and automation, unlike traditional networking, is a modern-day skill that helps in configuring, managing, and operating networks and network devices. This book will guide you with important information, helping you set up and start working with network programming and automation.With Network Programming and Automation Essentials, you'll learn the basics of networking in brief. You'll explore the network programming and automation ecosystem, learn about the leading programmable interfaces, and go through the protocols, tools, techniques, and technologies associated with network programming. You'll also master network automation using Python and Go with hands-on labs and real network emulation in this comprehensive guide.By the end of this book, you'll be well equipped to program and automate networks efficiently.What you will learnUnderstand the foundation of network programmingExplore software-defined networks and related familiesRecognize the differences between Go and Python through comparisonLeverage the best practices of Go and PythonCreate your own network automation testing framework using network emulationAcquire skills in using automation frameworks and strategies for automationWho this book is forThis book is for network architects, network engineers, and software professionals looking to integrate programming into networks. Network engineers following traditional techniques can use this book to transition into modern-day network automation and programming. Familiarity with networking concepts is a prerequisite.
R 1,531.00
Introduction to Python Programming and Data Structures, Global Edition
For introductory courses in Python Programming and Data Structures. A fundamentals first approach to programming helps students create efficient, elegant code. Introduction to Python Programming and Data Structures introduces students to basic programming concepts using a fundamentals-first approach that prepares students to learn object-oriented programming and advanced Python programming. This approach presents programming concepts and techniques that include control statements, loops, functions, and arrays before designing custom classes. Students learn basic logic and programming concepts prior to moving into object-oriented and GUI programming. The content incorporates a wide variety of problems with various levels of difficulty and covers many application areas to engage and motivate students.
R 3,391.00
R 1,282.00
R 763.00
R 641.00
R 611.00
R 1,099.00
